People

Michael Zeifman, Ph.D.

Principal Technical Staff, Building Energy Systems
Expertise:
  • Residential Energy Modeling and Disaggregation
  • Statistical Data Modeling and Analysis
  • Physics-Based Monte Carlo Simulations
  • Reliability and Uncertainty Characterization

Dr. Michael Zeifman is a Principal Member of Technical Staff for Fraunhofer CSE’s Building Energy Systems Group and specializes in interdisciplinary topics, such as application of advanced statistical and machine learning methods to energy monitoring and modeling, experimental design, demand response and uncertainty characterization. Prior to joining Fraunhofer CSE in 2010, Michael worked in the general field of modeling and simulation for more than fifteen years. He has served as a principal investigator on numerous R&D projects funded either by government or industry, as an Executive/Technical Program Committee member on several IEEE conferences, and as an NSF Panel Reviewer (Information and Intelligent Systems Division). Michael authored about 70 peer-reviewed scientific and technical papers.

Michael received his undergraduate degree in Engineering Physics from Peter the Great St. Petersburg Polytechnic University, Russia, and his graduate degrees in Quality Control and Reliability from Technion in Haifa, Israel. Michael is a Senior Member of both IEEE and AIAA.

Recent Presentations and Publications

Zeifman, M., Lazrak, A., Roth, K. (2019).
Residential retrofits at scale: opportunity identification, saving estimation, and personalized messaging based on communicating thermostat data. In: Energy Efficiency. : Springer, pp. 1-13.
https://doi.org/10.1007/s12053-019-09797-9
Zeifman, M., Lazrak, A., Roth, K. (2018).
Residential retrofits at scale: opportunity identification, saving estimation and personalized messaging based on communicating thermostat data. In: 2018 ACEEE Summer Study Proceedings. Washington D.C.: ACEEE, 12-1 to 12-13.
Annual energy savings of up to $4- 5 billion could be achieved n ationwide through basic insulation and heating system...
Zeifman, M. - August 16, 2018
Residential retrofits at scale: opportunity identification, saving estimation and personalized messaging based on communicating thermostat data. ACEEE 2018 Summer Study on Energy Efficiency in Buildings, ACEEE. Asilomar Conference Grounds, Pacific Grove, CA.
Michael Zeifman presented on Panel 12 - Smart Buildings, Smart Grid, and the Internet of Things on Aug. 16, Session 1,...
Kromer, M., Roth, K., Yip, T., Zeifman, M. - June 12, 2018
The SunDial Framework: Enabling High Penetration Solar through the Integration of Energy Storage, Demand Management, and Forecasting. World Conference on Photovoltaic Energy Conversion (WCPEC-7), IEEE. Hilton Waikoloa Village, Waikoloa, HI.
Tsz Yip presented.
Roth, K., Zeifman, M., Lazrak, A. - January 17, 2018
Whereat we have a Thermostat Chat: Using Communicating Thermostat Data to Remotely Identify EE Opportunities. CEE Winter Program Meeting, Consortium for Energy Efficiency (CEE). Hyatt Centric Fisherman's Wharf, San Francisco, CA.
Kurt Roth presents.
Zeifman, M. (2017).
United States Patent: Methods and system for nonintrusive load monitoring. : United States Patent Office.
Identification and tracking of major electric appliances by using aggregate power data obtained at the main breaker...
Lazrak, A., Zeifman, M. - November 9, 2017
Estimation of Physical Buildings Parameters Using Interval Thermostat Data. 4th ACM International Conference on Systems for Energy-Efficient Built Environments (BuildSys 2017) , ACM. Aula Conference Centre, Delft, Netherlands.
Amine Lazrak presented.
Zeifman, M., Kromer, M., Roth, K. (2017).
Integrated System to Enable High-Penetration Feeder-Level PV: Preliminary Design and Simulation Results. In: IEEE ISGT 2017. Washington: IEEE.
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Zeifman, M., Roth, K., Urban, B. (2017).
Communicating Thermostats as a Tool for Home Energy Performance Assessment. In: Proceedings of 35th IEEE International Conference on Consumer Electronics. Las Vegas: IEEE, pp. 191-192.
Zeifman, M., Roth, K. (2016).
Residential Remote Audits: Estimation of Building Thermal Parameters Using Interval Energy Consumption Data. In: Proceedings of ACEEE Summer Study on Energy Efficiency in Buildings Pacific Grove: ACEEE, pp. 12.1-12.12.
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Zeifman, M. - February 11, 2015
Smart Meter Data Predict Household Propensity to Enroll in Energy Efficiency Program. Association of Energy Services Professionals (AESP) National Conference and Expo, Association of Energy Services Professionals AESP. Hilton Orlando Lake Buena Vista, Orlando, FL.
Zeifman, M., Akers, C. (2015).
Nonintrusive Monitoring of Miscellaneous and Electronic Loads. In: 2015 IEEE International Conference on Consumer Electronics (ICCE). Las Vegas: IEEE, pp. 305-308.
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Zeifman, M. (2015).
Measurement and Verification of Energy Saving in Smart Building Technologies. In: Proceedings of IEEE Global Conference on Signal and Information Processing (GlobalSIP). Orlando: IEEE, pp. 343-347.
Abreu, J., Hardy, N., Pereira, F., Zeifman, M. (2015).
Modeling Human Reliability in the Power Grid Environment: an Application of the SPAR-H Methodology. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting. , pp. 1-5.
Harbor, D., Roth, K., Zeifman, M., Shmakova, V. (2015).
The Energy and Greenhouse Gas Emissions Impacts of Telecommuting and e-Commerce. Final Report by the Fraunhofer USA Center for Sustainable Energy Systems (CSE) to the Consumer Electronics Association. : Fraunhofer Center for Sustainable Energy Systems CSE, pp. 1-81.
Zeifman, M. (2014).
I Know What You Did Last Summer: Smart Meter Data Accurately Predict Household Intention to Enroll in Energy Efficiency Program. In: Behavior, Energy & Climate Change (BECC) . Washington: IEEE, pp. 1-17.
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Zeifman, M. (2014).
Smart meter data analytics: Prediction of enrollment in residential energy efficiency programs. In: 2014 International Conference on Systems, Man and Cybernetics (SMC). San Diego: IEEE, pp. 413-416.
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Zeifman, M. (2014).
Tutorial: Nonintrusive Appliance Load Monitoring - Opportunities and Challenges. In: 32nd 2014 International Conference on Consumer Electronics. Las Vegas: IEEE.
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Zeifman, M., Roth, K., Stefan, J. (2013).
Automatic Recognition of Major End-Uses in Disaggregation of Home Energy Display Data. In: 2013 International Conference on Consumer Electronics. Las Vegas, pp. 104-105.
Zeifman, M. (2012).
An Approximate Probabilistic Approach for Event-Based Disaggregation. In: 1st International Workshop on Non-Intrusive Load Monitoring. Pittsburgh.
Zeifman, M. (2012).
Disaggregation of Home Energy Display Data Using Probabilistic Approach. In: IEEE Transactions on Consumer Electronics. 58(1), Las Vegas: IEEE, pp. 23-31.
Zeifman, M., Roth, K. (2011).
Viterbi Algorithm with Sparse Transitions (VAST) for Nonintrusive Load Monitoring. In: IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG). Paris: IEEE, pp. 1-8.
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Zeifman, M., Roth, K. (2011).
Nonintrusive appliance load monitoring: Review and outlook. In: IEEE Transactions on Consumer Electronics 57(1), Las Vegas: IEEE, pp. 76-84.
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Contact

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Michael Zeifman, Ph.D.
Principal Technical Staff, Building Energy Systems
Office +1 (617) 714-6510
Email